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Universal Containers plans to upload target data from an external tool to CRM Analytics so it can calculate the sales team target attainments.
The target data changes every month, so the datasets need to be updated on a monthly basis. The target data is a CSV file that contains the Salesforce ID of the sales rep, the target amount, and the month of the target. For each sales rep, the file contains a target for every month of the current year as well as all previous years.
Based on this information, which operation should a consultant use with the Analytics External Data API to upload the file?
For uploading target data that changes on a monthly basis and includes historical data (previous years' targets), the appropriate operation is 'Overwrite.' This ensures that each time the CSV file is uploaded, the existing data in the dataset is replaced with the new data. This is critical because the target data includes both current and historical data, and using 'Overwrite' will update the entire dataset while maintaining historical accuracy.
'Append' would add new data without replacing the old records, leading to duplication, and 'Update' is not suitable for completely replacing data in this context.
Universal Containers' CRM Analytics team is building a dashboard with two widgets, and the queries use different datasets.
1. List widget associated to the query "Type_2" and grouped by the dimension "Type" (multi-selection)
2. Donut chart widget associated to the query "Query_pie_3" and grouped by the dimension "Type"
The team wants any selection in the List widget to filter the Donut chart and vice vers
a. Users should be able to choose more than one Type (multi-selection).
What is the recommended way to accomplish the required filtering?
A CRM Analytics consultant has enabled data sync manually in an org that uses dataflows/recipes. The client says that the dataflow/recipe fails each time it starts running.
What is causing the dataflow/recipe to fail?
A CRM Analytics consultant is asked to make changes to the current sales dashboard at Cloud Kicks. The dashboard is crucial to track the daily sales performance of the company and needs to be
available for other users while the consultant works on the changes.
How should the consultant proceed to update the dashboard?
Universal Containers' CRM Analytics team is building a dashboard with two widgets.
1. List widget associated to the query "Type_2" and grouped by the dimension "Type" (multi-selection)
2. Donut chart widget associated to the query "Step_pie_3" and grouped by the dimension "Type"
The team wants to use bindings/interactions so any selection in the List widget will filter the Donut chart. The queries use different datasets,
and users should be able to choose more than one Type (multi-selection).
What is the right syntax for the binding/interaction?
A)
B)
C)
For the given requirement where a selection in a list widget needs to filter data displayed on a donut chart, and considering the list allows for multi-selection of the 'Type', the correct binding/interaction would be to use a syntax that captures the multi-select aspect and passes it appropriately. The right syntax, as indicated in Option A, looks like this:
'{{column(Type_2.selection, [\'Type\']).asObject()}}'
This syntax ensures:
Multi-selection: The column() function in combination with .asObject() ensures that multiple selected values from the 'Type_2' query can be passed as an object, which the donut chart can utilize to filter its content.
Correct Data Type Handling: By using .asObject(), the binding ensures the data passed between widgets maintains the correct structure expected by the CRM Analytics dashboard, thereby ensuring accurate filtering.
